数据分析、机器学习、LLM 应用、提示词设计（8855 个）
Expert guide for Data Pipelines, ETL/ELT, and Analytics Engineering. Covers dbt, Apache Airflow, Dagster, BigQuery, ClickHouse, and DuckDB / Panduan ahli untuk Data Pipelines, ETL/ELT. Mencakup dbt, Airflow, Dagster, BigQuery, ClickHouse, dan DuckDB.
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Expert guide for Prompt Engineering, Chain-of-Thought, few-shot prompting, structured output, prompt injection defense, and automated AI evaluations & regression benchmarking (Promptfoo, DeepEval) / Panduan ahli rekayasa prompt dan evaluasi otomatis AI.
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Use when designing or implementing Spring Data JPA on Spring Boot 4 — repository boundaries, projections, query patterns, custom repositories, CQRS read models, entity relationships, or persistence performance fixes. Not for generic SQL help, database admin work, or project-wide migration (see the springboot-migration skill).
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Build applications with Univer Office SDK, covering the Web SDK (browser Office editors, headless Sheets and Docs in Node), Server SDK (self-hosted OT collaboration, storage, auth, Office import/export), AI SDK (agent-operated Office CLIs, reviewable Worktrees), and Binding SDK (plain HTML pages bound to live Sheet data). Use when starting or designing any Univer-based app or choosing Univer packages, including when the user describes a spreadsheet, document, collaboration, or AI-office need without naming a Univer package.
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Read your TikTok niche and audience from real data. Scan a hashtag for top videos with plays, likes, and comments, see which hooks and sounds are working, pull a profile's videos (yours or a competitor's), and read the commenters on a video (TikTok hides likers, so commenters are the signal). Powered by Apify, no login. Triggers on "what is trending on TikTok", "analyze this hashtag", "competitor videos", "read my comments", "which sounds are working". Not for writing a script (use tt-hook-scripter).
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Use when the user asks Codex to read or write Odysseus data (todos, email, calendar, memory, documents) or to launch/monitor/stop a Cookbook model-serve task through the scoped Codex Agent API. Requires ODYSSEUS_URL and ODYSSEUS_API_TOKEN.
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Use when the user asks Claude Code to read or write Odysseus data (todos, email, calendar, memory, documents) or to launch/monitor/stop a Cookbook model-serve task through the scoped Claude Agent API. Requires ODYSSEUS_URL and ODYSSEUS_API_TOKEN.
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Integrate Univer Sheets, Docs, or Slides into React, Vue 3, HTML, or Node.js projects. Use when embedding Univer, choosing preset or plugin mode, initializing instances, configuring themes/locales/workers, or manipulating workbooks, worksheets, ranges, formulas, permissions, and events through the Facade API.
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Use when modifying domain/models/, domain/services/, adaptor/llm/, or any business logic involving insurance terms, coverages, or risk rules. Also use when adding new fields, endorsements, or coverage types.
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Design insurance data analytics. TRIGGERS - Use when user needs help with insurance-data-analytics related tasks.
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Check the current status of the Strait of Hormuz — shipping transit data, oil price impact, stranded vessels, insurance risk levels, diplomatic developments, and global trade impact. Use this skill whenever the user asks about the Strait of Hormuz, Hormuz chokepoint, Persian Gulf shipping risk, oil transit disruption, war risk premium in the Gulf, Middle East shipping routes, tanker traffic through Hormuz, oil supply chain risk, or geopolitical risk affecting energy markets. Triggers include: "Hormuz status", "Strait of Hormuz", "is Hormuz open", "shipping through the Gulf", "oil chokepoint", "Persian Gulf tanker traffic", "war risk premium", "Hormuz crisis", "energy supply chain risk", "oil transit disruption", "Middle East shipping", any mention of Hormuz or Persian Gulf in context of oil, shipping, or geopolitical risk.
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Retrieves and analyzes FHIR Coverage and Organization resources to produce a structured insurance summary with coordination of benefits analysis. Use when user asks to "check insurance", "coverage details", "verify coverage", "insurance summary", "what plan is the patient on", "primary vs secondary insurance", or "coverage status". Do NOT use for clinical data, demographics beyond insurance, or billing claim submission.
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Analyze healthcare claims data for real-world evidence (RWE) studies. Use when working with medical/pharmacy claims (837/835), calculating utilization metrics, building patient cohorts, or analyzing treatment patterns. Triggers include claims data, RWE, real-world evidence, 837, 835, medical claims, pharmacy claims, utilization, treatment patterns, HEDIS, healthcare analytics.
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Provides domain knowledge and guidance for the Flare Data Connector (FDC)—attestation types, request flow, Merkle proofs, verifier/DA Layer, and smart contract integration. Use when working with FDC, cross-chain attestations, EVMTransaction, Web2Json, Payment, AddressValidity, proof-of-reserves, weather insurance, or Flare Developer Hub FDC guides and starter repos.
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Validate data quality in CSV/Excel files for vehicle insurance platform. Use when checking required fields, validating data formats, detecting quality issues, or generating quality reports. Mentions "validate", "check fields", "data quality", "missing values", or "quality score".
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Data governance strategy, quality validation rules, and data dictionary management for vehicle insurance platform. Use when defining data quality standards, implementing validation rules, managing field mappings, resolving data conflicts, or establishing data governance processes. Covers data cleaning standards, quality metrics, and mapping management.
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Clean and standardize vehicle insurance CSV/Excel data. Use when handling missing values, fixing data formats, removing duplicates, or standardizing fields. Mentions "clean data", "handle nulls", "standardize", "duplicates", or "normalize".
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Coterie Insurance integration. Manage data, records, and automate workflows. Use when the user wants to interact with Coterie Insurance data.
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Complete architecture reference for the A3 insurance platform — file locations, data flow, conventions, microservice map, and fullstack patterns
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Process vehicle insurance Excel data using Pandas - file handling, data cleaning, merging, validation. Use when processing Excel/CSV files, handling data imports, implementing business rules (negative premiums, zero commissions), debugging data pipelines, or optimizing Pandas performance. Keywords: data_processor.py, Excel, CSV, Pandas, merge, deduplication, date normalization.
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Query the Bear EHR database using the semantic layer. Use when asked about clients, billing, appointments, insurance, clinical data, procedures, scheduling, programs, staff, vitals, diagnoses, revenue, claims, or any data question about the Bear application.
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Analyzes vehicle insurance daily reports and signing lists. Use when user asks to analyze insurance data, generate business reports, check institution performance, monitor policy trends, or detect business anomalies. Handles Excel/CSV files with fields like premium, institution, customer type, and renewal status.
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SQL Server database design best practices, naming conventions, indexing strategies, and performance optimization for .NET applications using Microsoft.Data.SqlClient and EF Core.
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Generates Repository interfaces and implementations following the Repository pattern. Provides data access abstraction for aggregate roots with EF Core implementations.
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